Light-stimulated synaptic transistor based on two-dimensional/organic heterojunction for neuromorphic computing

Chao Han; Jiayue Han; He Yu; Jun Gou; Jun Wang

doi:10.1117/12.3017713

30 April 2024 Light-stimulated synaptic transistor based on two-dimensional/organic heterojunction for neuromorphic computing

Chao Han, Jiayue Han, He Yu, Jun Gou, Jun Wang

Author Affiliations +

Proceedings Volume 13154, Sixth Conference on Frontiers in Optical Imaging and Technology: Novel Detector Technologies; 131540C (2024) https://doi.org/10.1117/12.3017713
Event: Sixth Conference on Frontiers in Optical Imaging Technology and Applications (FOI2023), 2023, Nanjing, JS, China

Abstract

Neuromorphic computing has considerable potential in simulating the efficient information processing capabilities of the human brain. Implementing neuromorphic computing requires the development of artificial synaptic devices that mimic biological synapses, which are the basic for information processing, storage, and transmission in biological neural networks. Herein, we demonstrate a light-stimulated synaptic transistor (LSST) device based on graphene/hexagonal boron nitride (h-BN)/pentacene heterojunction for emulating the basic functions of the human brain. The LSST devices can detect light stimulus at a wavelength of 520 nm and exhibits a variety of typical synaptic properties, such as excitatory postsynaptic current, paired pulse facilitation, and transition from short-term memory to long-term memory. In addition, the LSST device is capable of simulating the learning and forgetting processes of the human brain. Based on the optically and electrically controlled conductivity modulation characteristics of the LSST device, we construct an artificial neural network for perform pattern recognition tasks, and recognition accuracy of handwritten digits is 88.5%. These results mean that our LSST devices have great potential for future applications in neuromorphic computing.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chao Han, Jiayue Han, He Yu, Jun Gou, and Jun Wang "Light-stimulated synaptic transistor based on two-dimensional/organic heterojunction for neuromorphic computing", Proc. SPIE 13154, Sixth Conference on Frontiers in Optical Imaging and Technology: Novel Detector Technologies, 131540C (30 April 2024); https://doi.org/10.1117/12.3017713

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KEYWORDS

Large Synoptic Survey Telescope

Heterojunctions

Brain

Artificial neural networks

Neurons

Transistors

Graphene

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